- 相關(guān)推薦
求解非線性化工過程魯棒數(shù)據(jù)校正的新方法
Abstract：Data reconciliation is an effective technique for providing accurate and consistent value for chemical process. However, the presence of gross errors can severely bias the reconciled results. Robust estimators can significantly reduce the effect of gross errors and yield less-biased results. In this article, a new method is proposed to solve the robust data reconciliation problem of nonlinear chemical process. By using several technologies including linearization method, penalty function, virtual observation equation, and equivalent weights method, the robust data reconciliation problem can be transformed into least squares estimator problem which leads to the convenience in computation. Simulation results in a nonlinear chemical process demonstrate the efficiency of the proposed method. 作者： 周凌柯[1] 蘇宏業(yè)[2] 褚健[2] Author： ZHOU Lingke[1] SU Hongye[2] CHU Jian[2] 作者單位： 南京科技大學(xué)浙江大學(xué) 期 刊： 中國化學(xué)工程學(xué)報（英文版） ISTICEISCI Journal： CHINESE JOURNAL OF CHEMICAL ENGINEERING 年，卷(期)： 2006, 14(3) 分類號： N94 Keywords： data reconciliation robust estimator equivalent weights method 機標(biāo)分類號： TG8 TG4 機標(biāo)關(guān)鍵詞： 求解 非線性 化工過程 數(shù)據(jù)校正 新方法 Data Reconciliation data reconciliation chemical process least squares estimator new method 基金項目： 國家自然科學(xué)基金，國家高技術(shù)研究發(fā)展計劃(973計劃) 求解非線性化工過程魯棒數(shù)據(jù)校正的新方法[期刊論文] 中國化學(xué)工程學(xué)報（英文版） --2006, 14(3)周凌柯 蘇宏業(yè) 褚健Data reconciliation is an effective technique for providing accurate and consistent value for chemical process. However, the presence of gross errors can severely bias the reconciled results. Robust es...【求解非線性化工過程魯棒數(shù)據(jù)校正的新方法】相關(guān)文章：
非線性PD型比例導(dǎo)引魯棒性研究04-27
神經(jīng)網(wǎng)絡(luò)融合信賴域求解非線性規(guī)劃的新方法04-29
基于LMI方法的一類非線性模糊脈沖系統(tǒng)的魯棒模糊控制04-26
數(shù)據(jù)挖掘過程中連續(xù)屬性離散化新方法研究04-29
一類離散的非線性切換系統(tǒng)的魯棒鎮(zhèn)定性問題04-28
外測數(shù)據(jù)處理中小波濾波的魯棒性算法研究04-28
非線性方程組的求解05-01